一、deeplearning-assignment 到目前为止,我们一直使用numpy来建立神经网络。这次作业将深入学习框架,可以更容易地建立神经网络。 TensorFlow,PaddlePaddle,Torch,Caffe,Keras等机器学习框架可以显著地加速机器学习开发。这些框架有很多文档,可以随意阅读。在本次任务中,将学习如何在TensorFlow中执行以下操作: 初始化变量 开始你...
Coursera 吴恩达《Machine Learning》视频 + 作业 红色石头的个人网站:www.redstonewill.com 吴恩达(Andrew Ng)在 Coursera 上开设的机器学习入门课《Machine Learning》,授课地址是: Coursera Andrew Ng Machine Learning 关于这门课的官方介绍是:本课程将广泛介绍机器学习、数据挖掘和统计模式识别。相关主题包括:(i) ...
What does that mean? (Please check all the answers, because all of them are correct!) 【正确】The DeepLearning.AI and Stanford Online teams would like to give you a round of applause! 【正确】You deserve to celebrate! 【正确】Andrew sends his heartfelt congratulations to you! 【正确】What...
【正确】见上图 第3 个问题:You have reached the final practice quiz of this class! What does that mean? (Please check all the answers, because all of them are correct!) 【正确】The DeepLearning.AI and Stanford Online teams would like to give you a round of applause! 【正确】You deserv...
Supervised Learning和unsupervised learning最重要的区别是“right answers” given,给了足够的samples,等同于上文的E,供电脑学习,通过举一反三得到未知的答案。 Supervised Learning又分成了两类:回归和分类 In aregressionproblem, we are trying to predict results within acontinuousoutput, meaning that we are try...
Machine Learning algorithms: -Supervised Learning -Unsupervised Learning Others: Reinforcement Learning, Recommender Systems Supervised Learning Example 1: Housing price prediction Supervised learning:(right answers are given)we are given a data set and already know what our correct output should look like...
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补充：[Machine Learning Engineering for Production (MLOps)]Specialization.DeepLearning.AI的出品。无论...
Supervised machine learning, commonly known as supervised learning , refers to algorithms that learn the mapping from input to output. (X -> Y) The key feature of supervised learning is providing the algorithm with examples to learn from, including the correct answers. ( training set ) By co...
therefore it must be superior to y(1) in order to satisfy the decreasing trend of the data. Among the proposed answers, the only one that meets both the conditions is hθ(x)=−569.6−530.9x. We can better appreciate these considerations observing the graph of the training data and ...